Spatiotemporal Changes in Extreme Temperature and Precipitation Events in the Three‐Rivers Headwater Region, China

Yang, Xi; Miao, Chiyuan; Wu, Jingwen; Duan, Qingyun; Lei, Xiaohui; Li, Hu

doi:10.1029/2017jd028226

Cited by 58 publications

(23 citation statements)

References 76 publications

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“…The simulations of future scenarios by climate models show a decrease in the duration of mid-latitude precipitation extremes and changes in the zonal extent of both signs depending on latitude 12 . Observations confirm the changing temporal distribution of heavy rain events 13–15 . The frequency and duration of rainstorms are increasing over the Indian landmass 16 .…”

Section: Introductionsupporting

confidence: 69%

Recent spatial aggregation tendency of rainfall extremes over India

Nikumbh

Chakraborty

Bhat

2019

Sci Rep

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Significant increase in the frequency of occurrences of rainfall extremes has been reported over several parts of the world. These extreme events were defined at individual grids without considering their spatial extent. Here, using ground-based observations over India during boreal summer, we show that the average size of spatially collocated rainfall extremes has been significantly increasing since 1980. However, the frequency of occurrences of such collocated extreme events remains unchanged. Around 90% of the total number of large-sized events (area ≥ 70 × 10 3 km 2 ) of our study period (1951 to 2015) have occurred after 1980. Some of the major floods in recent decades over India are attributed to these large events. These events have distinctive precursory planetary-scale conditions, unlike their smaller counterparts. As the underlying physical mechanisms of extremes rainfall events are size-dependent, their changing spatial extent needs to be considered to understand the observed trends correctly and obtain realistic future projections.

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Section: Introductionsupporting

confidence: 69%

Recent spatial aggregation tendency of rainfall extremes over India

Nikumbh

Chakraborty

Bhat

2019

Sci Rep

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“…We observe that there are no significant variations in annual precipitation after the year 1991 (the change-point year based on the M-K abrupt change test) ( Figure S1a), whereas for temperature, there are straightforward M-K variations for annual mean, minimum, and maximum temperatures ( Figure S1b-d). As compared with our previous research [41], the frequency of occurrence of daily precipitation of more than 10 mm showed an upward trend. At the same time, the amount of precipitation did not change greatly, which means that the occurrence of dry days also showed an upward trend.…”

Section: Temporal Pattern Of Long-term Observed Variablescontrasting

confidence: 44%

SWAT-Based Runoff Simulation and Runoff Responses to Climate Change in the Headwaters of the Yellow River, China

Zheng

Yang

2019

Atmosphere

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Runoff in snowy alpine regions is sensitive to climate change in the context of global warming. Exploring the impact of climate change on the runoff in these regions is critical to understand the dynamics of the water cycle and for the improvement of water resources management. In this study, we analyzed the long-term variations in annual runoff in the headwaters region of the Yellow River (HRYR) (a typical snowy mountain region) during the period of 1956-2012. The Soil and Water Assessment Tool (SWAT) with different elevation bands was employed to assess the performance of monthly runoff simulations, and then to evaluate the impacts of climate change on runoff. The results show that the observed runoff for the hydrological stations at lower relative elevations (i.e., Maqu and Tangnaihai stations) had a downward trend, with rates of 1.91 and 1.55 mm/10 years, while a slight upward trend with a rate of 0.26 mm/10 years was observed for the hydrological station at higher elevation (i.e., Huangheyan station). We also found that the inclusion of five elevation bands could lead to more accurate runoff estimates as compared to simulation without elevation bands at monthly time steps. In addition, the dominant cause of the runoff decline across the whole HRYR was precipitation (which explained 64.2% of the decrease), rather than temperature (25.93%).

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“…The atmospheric moisture content will increase accompanying with the increased water-holding capacity with warming (Karl & Trenberth, 2003;Soden et al, 2005) and consequently enhance extreme precipitation (O'Gorman & Schneider, 2009;Trenberth, 1999). Intensification of East Asian climate system, as well as the changes in Antarctic Oscillation, Arctic Oscillation, Indian Summer Monsoon, and North Atlantic Oscillation, have significant correlation with the increases in precipitation extremes over China (Chen, 2013;Chen et al, 2010;Gong et al, 2011;Sun et al, 2008;Sundaram et al, 2012;Tong et al, 2006;Xi et al, 2018;Zhao et al, 2012). Although increasing trend of extreme precipitation shows in both dry and wet regions, distinct difference exists between dry and wet regions.…”

Section: Discussionmentioning

confidence: 99%

Changes in Extreme Precipitation Over Dry and Wet Regions of China During 1961‐2014

Han

et al. 2019

JGR Atmospheres

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Changes in extreme precipitation differ among regions (e.g., dry and wet regions), causing different adverse effects on human life, social economy, and natural ecosystems on a warming planet. In this study, we use the 95th percentile‐based threshold to define extreme precipitation. The spatiotemporal changes in extreme precipitation and temperature‐extreme precipitation scaling relationship between dry and wet regions of mainland China during 1961‐2014 are analyzed using two gridded data sets of precipitation and temperature observations. Extreme precipitation increased faster in dry regions (3.9% frequency and 2.8% relative intensity per decade) compared to wet regions (2.5% frequency and 2.1% relative intensity per decade) over the past 54 years. Despite the negative regression relationship between mean precipitation and temperature in wet regions, extreme precipitation has a positive relationship with temperature. The regression coefficient in relative intensity against temperature change is 6% per °C in wet regions. The frequency increases significantly (p < 0.01) faster as temperature increases in wet regions (11.1% per °C) compared with dry regions (6.9% per °C). These results suggest that precipitation extremes increase for both dry and wet regions, and faster trends are observed in dry regions. However, the same magnitude of warming causes more extreme precipitation in wet regions. Therefore, more extreme precipitation in future may raise the risk of flooding in both dry and wet regions, particularly for wet regions, due to the stronger relative intensity and faster increases against warming.

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Spatiotemporal Changes in Extreme Temperature and Precipitation Events in the Three‐Rivers Headwater Region, China

Cited by 58 publications

References 76 publications

Recent spatial aggregation tendency of rainfall extremes over India

Recent spatial aggregation tendency of rainfall extremes over India

SWAT-Based Runoff Simulation and Runoff Responses to Climate Change in the Headwaters of the Yellow River, China

Changes in Extreme Precipitation Over Dry and Wet Regions of China During 1961‐2014

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